This invention is related to wireless networks, and in particular to a method and apparatus to incorporate channel state information (CSI) in demodulating and decoding a received signal in an orthogonal frequency division multiplexing (OFDM) radio receiver.
Wireless local area network (WLAN) standards that use OFDM have recently become popular. Such standards include variants of the IEEE 802.11 standard such as IEEE 802.11a in the 5 GHz frequency range and 802.11g in the 2.4 GHz frequency range. In an OFDM radio transmitter, a signal for transmission is split into a set of subcarriers (also called “tones”) that are each modulated then combined and transmitted wirelessly via a wireless channel. At the receiving end, the received signal is split into the various subcarriers that are then demodulated and decoded to produce the received signal. An OFDM transmitter typically uses the inverse discrete Fourier transform (IDFT), typically implemented as an inverse Fast Fourier Transform (IFFT), to combine the subcarriers for transmission, and an OFDM receiver typically uses the forward discrete Fourier transform (DFT), typically implemented as a Fast Fourier Transform (FFT) to form the received subcarriers from the received signal. Each of the subcarriers experiences a different channel.
OFDM transmitters typically use forward error correction and/or convolutional coding, and thus are tolerant of noise present in each of the subcarriers. In the presence of Rayleigh fading, the channels for some of the subcarriers may have a lower amplitude response than others. In some cases, some of the subcarriers may have a response so low that their signal-to-noise ratios are extremely low. Thus, in OFDM, the various subcarriers will have different signal-to-noise ratios (SNRs) as a result of the different quality of the respective channels. For example, a subcarrier that falls into a notch in the frequency response will include mostly noise; one in a peak will suffer much less from noise. Thus, data items conveyed by subcarriers that pass through a relatively high quality channel and thus have a relatively high SNR are a priori more reliable than those conveyed by subcarriers that pass through relatively low quality channels and thus have low SNRs. This extra a priori information is usually known as channel-state information (CSI). The channel-state information concept similarly embraces interference which can affect carriers selectively, just as noise does.
When knowledge about the reliability of each of the channels of the subcarriers is used in the decoding process, e.g., when unreliable subcarriers are trusted less, the packet error rate performance improves significantly in the presence of fading.
Including channel-state information in decoding, e.g., in the generation of soft decisions is known in the art. See for example, J. H. Stott: “Explaining some of the magic of COFDM,” Proceedings of 20th International Television Symposium 1997, Montreux, Switzerland, in which it is stated:                “Including channel-state information in the generation of soft decisions is the key to the unique performance of COFDM in the presence of frequency-selective fading and interference.”        
See also J. H. Stott: “The How and Why of COFDM,” European Broadcast Union (EBU) Technical Review, Winter, 1998. COFDM stands for coded OFDM.
The present invention is related to using channel state information in a practical receiver for use in a WLAN that uses OFDM.
It is known to detect “null” channels using the estimated channel response and not use the subcarriers of the null channels.
In a typical OFDM WLAN transmitter, to protect the data from the channel, the packet data is channel encoded with a convolutional code and modulated onto the subcarriers. In a typical OFDM WLAN receiver, a FFT processor determines the individual subcarriers. A channel estimator and equalizer equalizes the subcarrier for their different respective channels, and a demodulator demodulates the equalized subcarrier signals. The demodulator forms soft decisions rather than hard decisions. The soft decision data is passed to a decoder, e.g., a Viterbi decoder.
When CSI is incorporated, the soft decision data is weighted based on channel metrics so that data from subcarriers of relatively poor quality, e.g., of relatively poor quality channels will have less of an impact on the decoding process of the Viterbi decoder.
U.S. Pat. No. 6,442,130 titled SYSTEM FOR INTERFERENCE CANCELLATION to inventors Jones, et al., and assigned to the assignee of the present invention, describes one prior art system that uses CSI. U.S. Pat. No. 6,442,130 is incorporated herein by reference. While the prior art receiver described in U.S. Pat. No. 6,442,130 uses multiple antennas and spatial processing, the channel state information aspects are applicable to a receiver with a single antenna, not just to one that includes spatial processing. The CSI aspects of the receiver described in U.S. Pat. No. 6,442,130 (“the '130 receiver”) will therefore be used to illustrate a typical prior art receiver that uses CSI.
The '130 receiver includes a FFT processor that determines each subcarrier, a channel estimator that determines the channel response for each of the subcarriers, and a demodulator (called a symbol estimation block) to determine the symbol for each subcarrier. A noise and interference estimation block estimates the noise and interference at each subcarrier's channel and includes the demodulator. The noise and interference estimation block determines a measure of the difference between the equalized received signal and the nearest constellation point for the modulation scheme used to modulate the signal.
The multiple antenna version of the '130 receiver includes a statistical characterization block that develops a statistical characterization of the interference and noise among the antennas. This block is not needed in the single antenna case of the '130 receiver. In that case, the noise and interference estimation block is followed by a cost metric processor that generates the soft decisions as well as a cost metric value for each soft decision for each subcarrier. The cost metric value is a measure of the signal to noise ratio of the subcarrier signal of the channel. The cost metric value is used by a Viterbi decoder to decode the subcarrier signal. Thus, this cost value metric is the CSI. A simplified embodiment weights soft decisions by the CSI measure and inputs the weighted soft decisions to a Viterbi decoder that uses conventional Viterbi decoder metrics.
The determination of the CSI used in the '130 receiver is relatively complex requiring an estimate of the signal-to-interference-and-noise-ratio (SINR), which in turn required an estimate of the signal power and an estimate of the noise and/or interference power. Determining noise power is a computationally intense process. U.S. Pat. No. 6,442,130 obtains a measure of the noise power obtaining a measure of the distance in the I-Q plane between a signal and its nearest decision point. This quality of this measure of noise decreases the lower the signal-to-noise ratio because the lower the signal-to-noise ratio, the more decision errors are made. A decision error leads to a large error in the noise estimate because the nearest decision point is no longer the correct decision point. Therefore, prior art systems such as that in the '130 receiver work best in a high SINR environment. The OFDM variants of the IEEE 802.11 standard, e.g., the IEEE 802.11a standard need to be able to operate in a relatively low signal-to-noise ratio environment. Thus there is a need for a method of using CSI that works in a relatively low signal-to-noise ratio environment.
Furthermore, when an estimate of the relative amount of noise or the relative amount of interference in each channel is used, averaging is usually used to increase the quality of the noise estimate. In the '130 receiver, the channel confidence value is averaged. Furthermore the interference energy is smoothed across frequency or over successive bursts as part of the spatial processing. Also, one can smooth over successive bursts. For example, one may use an exponential window to incorporate values of previous bursts.
Thus, the prior art application of CSI, e.g., in the '130 receiver requires computationally intense calculations.
WLAN devices are typically used in portable battery operated equipment. Additionally, WLAN access points, although wired, are typically powered “in-line,” e.g., over Ethernet from a switch or router, and the amount of such in-line power is usually limited. Thus, there is a requirement for such WLAN equipment to have relatively low power consumption. There further is a need for such equipment to be relatively inexpensive. The computational complexity of prior art methods such as that of the '130 receiver are unsuitable for low-power and/or low cost solutions. A low cost solution, for example, is one that can be incorporated in a low power integrated circuit that implements a radio for WLAN applications.
Many of the techniques in the prior art can take a long time to estimate CSI metrics, even as long as 1 ms or more. There is a need in the art to determine a CSI metric relatively quickly.
There thus is a need in the art for an apparatus and method of using CSI that is relatively computationally simple. There further is a need in the art for an apparatus and method of using CSI that does not require estimating the relative amount of noise or the relative amount of interference in each channel. There further is a need in the art for an apparatus and method of using CSI that works well in a low signal-to-noise environment. There further is a need in the art to determine a CSI metric relatively quickly.